diff --git a/Problem1.py b/Problem1.py
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+## Problem1 
+# N Queens(https://leetcode.com/problems/n-queens/)
+
+
+# N -- No. of Rows and No. of Cols
+# Time Complexity : O(N * N!) = O((N + 1)!) = O(N!)
+# For each row we have N * (N - 2) * (N - 4) * (N - 6) =  N factorial = N! options
+# For each cell we check isSafe function. TC for isSafe function = O(N) -- Linear
+# TC for is safe function --- O(2 * N) * All possible combinations
+# So O(N) --- to check queen in same column above
+# O(N) --- Right diagonal up + Left Diagonal Up
+
+# Space Complexity : O(N^2) -- storing the grid
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+
+
+# Your code here along with comments explaining your approach in three sentences only
+# We exhaustively explore all possible combinations to place the queen. We know only one queen can come in a single row. So exhautively
+# for each row we go through all the cells(columns) and check if it is safe to put a queen there. If it is safe we put the queen at that cell
+# and recurse to the next row. When we have completed all the rows, it means all the queens have been placed. Then we make our valid matrix
+# as required in the question and append to the result. The isSafe function checks if the queen can be placed at the given cell or not. There
+# are 3 cases to check -- same column all the above rows from the current row, diagonaly right up and diagonally left up.
+
+class Solution(object):
+    def solveNQueens(self, n):
+        """
+        :type n: int
+        :rtype: List[List[str]]
+        """
+        # check if we can place the queen at cell (i, j) safely
+        def isQueenSafe(rowNo, colNo, board):
+            # check same column above
+            for i in range(rowNo):
+                if(board[i][colNo] == "Q"):
+                    return False
+
+            # check diagonal up left
+            r = rowNo - 1
+            c = colNo - 1
+            while((r >= 0) and (c >= 0)):
+                if(board[r][c] == "Q"):
+                    return False
+                r -= 1
+                c -= 1
+
+            # check diagonal up right
+            r = rowNo - 1
+            c = colNo + 1
+            while((r >= 0) and (c < len(board[r]))):
+                if(board[r][c] == "Q"):
+                    return False
+                r -= 1
+                c += 1
+
+            return True
+
+        # exhaustive function to place the queens
+        def helper(board, rowNo, allPossRes):
+            # base case
+            if(rowNo == len(board)):
+                # we have placed all the queens successfully
+                newRes = []
+                for m in range(len(board)): #O(N) -- rows
+                    newRes.append("".join(board[m])) # O(N) for each join
+
+                allPossRes.append(newRes)
+                return
+
+            # logic
+            # for a row checking each cell(column) if we can place the queen
+            for k in range(len(board)):
+                if(isQueenSafe(rowNo, k, board)):
+                    # yes it is safe
+
+                    # action
+                    board[rowNo][k] = "Q"
+                    # so recurse in the next row
+                    helper(board, rowNo + 1, allPossRes)
+                    # backtrack
+                    board[rowNo][k] = "."
+
+        # create the chess board
+        board = []
+        for i in range(n):
+            row = []
+            for j in range(n):
+                row.append(".")
+
+            board.append(row)
+
+        allPossRes = []
+        helper(board, 0, allPossRes)
+        return allPossRes
+
+
+sol = Solution()
+print(sol.solveNQueens(1))
+print(sol.solveNQueens(2))
+print(sol.solveNQueens(3))
+print(sol.solveNQueens(4))
+print(sol.solveNQueens(5))
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diff --git a/Problem2.py b/Problem2.py
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+## Problem2
+# Word Search(https://leetcode.com/problems/word-search/)
+
+# Method-1: Using void based recursion
+# M -- No. of Rows
+# N -- No. of Cols
+# L -- Length of the word
+# Time Complexity : O((M*N) * (3 ^ (L)))
+# TC: 3 ^ (L) --- for one DFS and we can have total M*N DFS
+
+# Space Complexity : O(L) = O(L) -- recursive stack
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+
+# Your code here along with comments explaining your approach in three sentences only
+# Wherever we match the first letter of the word to be searched in the grid, we start a fresh DFS. We have to keep track of our current path
+# that is visited cells as reusing a used cell is not allowed. So when the recursion returns we need to backtrack the action of making the 
+# cell visited, so that we can explore other paths from there. As other path could give us the word we are searching. For visited we are 
+# temporarily changing the state of the matrix to #. At each node we have 3 options to explore as we go deep into the tree. Max depth
+# of this tree would be the length of the word we are seaching. Here the input matrix remains preserved
+
+class Solution(object):
+    def __init__(self):
+        self.isWordFound = False
+    def exist(self, board, word):
+        """
+        :type board: List[List[str]]
+        :type word: str
+        :rtype: bool
+        """
+        if(len(word) > (len(board) * len(board[0]))):
+            # word length > matrix length
+            return False
+        
+        def helper(board, word, strIdx, row, col, dirs):
+            # base
+            # first check if word has been found. this condition should come first
+            if(strIdx == len(word)):
+                # word found
+                self.isWordFound = True
+                return
+                            
+            # bounds and visited check
+            if((row < 0) or (row >= len(board)) or (col < 0) or (col >= len(board[row])) or (board[row][col] == "#")):
+                return
+
+            if(self.isWordFound):
+                # word already found
+                return
+
+            if(board[row][col] == word[strIdx]):
+                # then only proceed further
+                # action
+                board[row][col] = "#"
+                # till now word is matching, lets recurse further
+                for k in range(len(dirs)):
+                    nr = row + dirs[k][0]
+                    nc = col + dirs[k][1]
+                    # recurse
+                    helper(board, word, strIdx + 1, nr, nc, dirs)
+                    # if(self.isWordFound):
+                    #     # word already found
+                    #     return
+                
+                # backtrack
+                board[row][col] = word[strIdx]
+
+        m = len(board)
+        n = len(board[0])
+        dirs = [(0, 1), (1, 0), (0, -1), (-1, 0)]
+        self.isWordFound = False
+        for i in range(m):
+            for j in range(n):
+                if(board[i][j] == word[0]):
+                    # start a fresh DFS
+                    
+                    helper(board, word, 0, i, j, dirs)
+                    if(self.isWordFound):
+                        # word already found
+                        return True
+        
+
+        return False
+    
+sol = Solution()
+print("Method-1: Using void based recursion")
+print(sol.exist([["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], "ABCCED"))
+print(sol.exist([["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], "SEE"))
+print(sol.exist([["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], "ABCB"))
+print(sol.exist([["A","E","E","D"],["S","F","C","S"],["A","D","E","E"]], "SFCEESDEE"))
+
+# Method-2: Using boolean based recursion
+# M -- No. of Rows
+# N -- No. of Cols
+# L -- Length of the word
+# Time Complexity : O((M*N) * (3 ^ (L)))
+# TC: 3 ^ (L) --- for one DFS and we can have total M*N DFS
+
+# Space Complexity : O(L) = O(L) -- recursive stack
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+
+# Your code here along with comments explaining your approach in three sentences only
+# The logic is exactly same. Just here we are using boolean based recursion. Here the input matrix changes as all the actions might not get 
+# backtracked
+
+class Solution(object):
+    def exist(self, board, word):
+        """
+        :type board: List[List[str]]
+        :type word: str
+        :rtype: bool
+        """
+        if(len(word) > (len(board) * len(board[0]))):
+            # word length > matrix length
+            return False
+        
+        def helper(board, word, strIdx, row, col, dirs):
+            # base
+            # first check if word has been found. this condition should come first
+            if(strIdx == len(word)):
+                # word found
+                return True
+                            
+            # bounds and visited check
+            if((row < 0) or (row >= len(board)) or (col < 0) or (col >= len(board[row])) or (board[row][col] == "#")):
+                return False
+
+            if(board[row][col] == word[strIdx]):
+                # then only proceed further
+                # action
+                board[row][col] = "#"
+                # till now word is matching, lets recurse further
+                for k in range(len(dirs)):
+                    nr = row + dirs[k][0]
+                    nc = col + dirs[k][1]
+                    # recurse
+                    if(helper(board, word, strIdx + 1, nr, nc, dirs)):
+                        return True
+                
+                # backtrack
+                board[row][col] = word[strIdx]
+
+            return False
+
+        m = len(board)
+        n = len(board[0])
+        dirs = [(0, 1), (1, 0), (0, -1), (-1, 0)]
+        for i in range(m):
+            for j in range(n):
+                if(board[i][j] == word[0]):
+                    # start a fresh DFS
+                    
+                    if(helper(board, word, 0, i, j, dirs)):
+                        return True
+                    
+        return False
+    
+sol = Solution()
+print("Method-2: Using boolean based recursion")
+print(sol.exist([["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], "ABCCED"))
+print(sol.exist([["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], "SEE"))
+print(sol.exist([["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], "ABCB"))
+print(sol.exist([["A","E","E","D"],["S","F","C","S"],["A","D","E","E"]], "SFCEESDEE"))
+
+